Dampak Hibah Pariwisata terhadap Kinerja Industri Pariwisata Jawa Tengah dan Daerah Istimewa Yogyakarta
Bibliographic record
Abstract
Keberlangsungan industri pariwisata khususnya hotel dan restoran di Jawa Tengah dan D.I Yogyakarta saat pandemi Covid-19 sangat penting karena memiliki dampak simultan terhadap kondisi sosial dan ekonomi. Melalui kebijakan stimulasi keuangan bagi pelaku industri pariwisata hotel dan restoran diharapkan supaya usaha tersebut dapat bertahan disaat jumlah kunjungan wisata menurun dan mempersiapkan upaya pemulihan saat pemberlakuan kebiasaan baru termasuk di kegiatan industri pariwisata melalui penyaluran hibah pariwisata. Mengingat peruntukan dana hibah tersebut diharapkan dapat memberikan stimulasi dan penyesuaian menuju kebiasaan baru industri pariwisata kajian empiris dengan pendekatan Analisis Kuantitatif Efisiensi dengan Frontier Analysis (FA) dan Structural Equation Modelling (SEM) terhadap 116 pelaku pariwisata hotel dan restoran, menunjukkan bahwa pemberian dana Hibah Pariwisata di Wilayah Provinsi Jawa Tengah dan D.I Yogyakarta memberikan efek positif terutama pada efisinesi alokasi kinerja keuangan yang diperoleh atas alokasi biaya gaji karyawan dan biaya operasional untuk meningkatkan efisiensi output berupa penerimaan hotel dan restoran.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.058 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".